3D quantification of NASH-related liver fibrosis using open-top light-sheet microscopy

使用开顶光片显微镜对 NASH 相关肝纤维化进行 3D 定量

基本信息

批准号：
10325461
负责人：
Nicholas Reder
金额：
$ 26.94万
依托单位：
ALPENGLOW BIOSCIENCES, INC.
依托单位国家：
美国
项目类别：
财政年份：
2021
资助国家：
美国
起止时间：
2021-09-20 至 2023-08-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10325461
关键词：
3-Dimensional Affect Aftercare Archives Biological Assay Biopsy CLIA certified Categories Cell Nucleus Cirrhosis Clinical Clinical Data Clinical Trials Collagen Complex Computer software Custom Cytoplasm Data Data Set Detection Diagnostic Diagnostic radiologic examination Disease Outcome Esters Evaluation Failure Fibrosis Formalin Future Gold Histologic Human Image Imaging Techniques Light Liver Liver Fibrosis Machine Learning Magnetic Resonance Imaging Malignant neoplasm of prostate Manuals Methods Microscope Microscopy Outcome Outcome Measure Pathologic Pathology Patients Pharmacotherapy Phase Population Positioning Attribute Preparation Prevalence Primary carcinoma of the liver cells Process Protocols documentation Readiness Research Sampling Sampling Errors Services Sirius Red F3B Small Business Innovation Research Grant Stains Techniques Technology Testing Therapeutic Agents Three-Dimensional Imaging Three-dimensional analysis Tissues Training Translating Trichrome stain United States Universities Washington Work algorithm training analysis pipeline antifibrotic treatment chronic liver disease drug candidate drug efficacy elastography high risk human tissue improved lightspeed liver biopsy machine learning algorithm mortality non-alcoholic fatty liver disease nonalcoholic steatohepatitis primary endpoint primary outcome sample archive secondary outcome three dimensional structure three-dimensional visualization

项目摘要

Abstract Non-alcoholic fatty liver disease (NAFLD) prevalence is estimated at >25% in the U.S., making it the most common cause of chronic liver disease. Non-alcoholic steatohepatitis (NASH), the progressive form of NAFLD, affects 1-3% of the U.S. population and is expected to double by 2030. Currently, there is no effective pharmacotherapy for NAFLD, but there are numerous promising drug candidates being evaluated in clinical trials. However, the primary endpoint for these trials, histologic fibrosis, has shortcomings including sampling error and use of a subjective five category scale to quantify a continuous variable. Our team has pioneered the use of 3D open-top light-sheet (OTLS) microscopy, which enables rapid, high-throughput imaging of large clinical samples. In combination with cutting-edge machine learning techniques, we hypothesize that 3D OTLS microscopy can provide more accurate and consistent assessment of fibrosis in liver biopsies from NASH patients. We will test this hypothesis by developing a multiplex staining protocol and machine learning analysis pipeline, which will be piloted on 20 archived FFPE liver biopsies. Results from our assay will be correlated with currently used primary and secondary outcome measures to motivate further studies with sing archived samples from clinical trials with responsivity and outcomes data.

抽象的非酒精性脂肪肝病（NAFLD）患病率估计在美国> 25％，使得这是慢性肝病的最常见原因。非酒精性脂肪性肝炎（NASH）， NAFLD的渐进形式影响美国人口的1-3％，预计将翻一番 2030年。目前，NAFLD没有有效的药物治疗，但是有很多在临床试验中评估有希望的候选药物。但是，是这些试验，组织学纤维化，存在缺点，包括抽样误差和使用主观五类量表以量化连续变量。我们的团队开创了使用 3D开放式灯页（OTL）显微镜，可实现快速，高通量成像的大型临床样本。结合最先进的机器学习技术，我们假设3D OTLS显微镜可以提供更准确，更一致的评估 NASH患者的肝活检中的纤维化。我们将通过开发一个多重染色协议和机器学习分析管道，该管道将在20 存档的FFPE肝活检。我们测定的结果将与当前使用的唱歌存档的主要和次要结果措施以激发进一步的研究来自具有响应性和结果数据的临床试验的样本。